pg_auto_failover Fault Tolerance¶
At the heart of the pg_auto_failover implemetation is a State Machine. The state machine is driven by the monitor, and its transitions are implemented in the keeper service, which then reports success to the monitor.
The keeper is allowed to retry transitions as many times as needed until they succeed, and reports also failures to reach the assigned state to the monitor node. The monitor also implements frequent health-checks targeting the registered PostgreSQL nodes.
When the monitor detects something is not as expected, it takes action by assigning a new goal state to the keeper, that is responsible for implementing the transition to this new state, and then reporting.
The pg_auto_failover monitor is responsible for running regular health-checks with
every PostgreSQL node it manages. A health-check is successul when it is
able to connect to the PostgreSQL node using the PostgreSQL protocol
(libpq), imitating the
How frequent those health checks are (20s by default), the PostgreSQL connection timeout in use (5s by default), and how many times to retry in case of a failure before marking the node unhealthy (2 by default) are GUC variables that you can set on the Monitor node itself. Remember, the monitor is implemented as a PostgreSQL extension, so the setup is a set of PostgreSQL configuration settings:
SELECT name, setting FROM pg_settings WHERE name ~ 'pgautofailover\.health'; name | setting -----------------------------------------+--------- pgautofailover.health_check_max_retries | 2 pgautofailover.health_check_period | 20000 pgautofailover.health_check_retry_delay | 2000 pgautofailover.health_check_timeout | 5000 (4 rows)
The pg_auto_failover keeper also reports if PostgreSQL is running as expected. This
is useful for situations where the PostgreSQL server / OS is running fine
and the keeper (
pg_autoctl run) is still active, but PostgreSQL has failed.
Situations might include File System is Full on the WAL disk, some file
system level corruption, missing files, etc.
Here’s what happens to your PostgreSQL service in case of any single-node failure is observed:
Primary node is monitored unhealthy
When the primary node is unhealthy, and only when the secondary node is itself in good health, then the primary node is asked to transition to the DRAINING state, and the attached secondary is asked to transition to the state PREPARE_PROMOTION. In this state, the secondary is asked to catch-up with the WAL traffic from the primary, and then report success.
The monitor then continues orchestrating the promotion of the standby: it stops the primary (implementing STONITH in order to prevent any data loss), and promotes the secondary into being a primary now.
Depending on the exact situation that triggered the primary unhealthy, it’s possible that the secondary fails to catch-up with WAL from it, in that case after the PREPARE_PROMOTION_CATCHUP_TIMEOUT the standby reports success anyway, and the failover sequence continues from the monitor.
Secondary node is monitored unhealthy
When the secondary node is unhealthy, the monitor assigns to it the state CATCHINGUP, and assigns the state WAIT_PRIMARY to the primary node. When implementing the transition from PRIMARY to WAIT_PRIMARY, the keeper disables synchronous replication.
When the keeper reports an acceptable WAL difference in the two nodes again, then the replication is upgraded back to being synchronous. While a secondary node is not in the SECONDARY state, secondary promotion is disabled.
Monitor node has failed
Then the primary and secondary node just work as if you didn’t have setup pg_auto_failover in the first place, as the keeper fails to report local state from the nodes. Also, health checks are not performed. It means that no automated failover may happen, even if needed.
Adding to those simple situations, pg_auto_failover is also resilient to Network Partitions. Here’s the list of situation that have an impact to pg_auto_failover behavior, and the actions taken to ensure High Availability of your PostgreSQL service:
Primary can’t connect to Monitor
Then it could be that either the primary is alone on its side of a network split, or that the monitor has failed. The keeper decides depending on whether the secondary node is still connected to the replication slot, and if we have a secondary, continues to serve PostgreSQL queries.
Otherwise, when the secondary isn’t connected, and after the NETWORK_PARTITION_TIMEOUT has elapsed, the primary considers it might be alone in a network partition: that’s a potential split brain situation and with only one way to prevent it. The primary stops, and reports a new state of DEMOTE_TIMEOUT.
The network_partition_timeout can be setup in the keeper’s configuration and defaults to 20s.
Monitor can’t connect to Primary
Once all the retries have been done and the timeouts are elapsed, then the primary node is considered unhealthy, and the monitor begins the failover routine. This routine has several steps, each of them allows to control our expectations and step back if needed.
For the failover to happen, the secondary node needs to be healthy and caught-up with the primary. Only if we timeout while waiting for the WAL delta to resorb (30s by default) then the secondary can be promoted with uncertainty about the data durability in the group.
Monitor can’t connect to Secondary
As soon as the secondary is considered unhealthy then the monitor changes the replication setting to asynchronous on the primary, by assigning it the WAIT_PRIMARY state. Also the secondary is assigned the state CATCHINGUP, which means it can’t be promoted in case of primary failure.
As the monitor tracks the WAL delta between the two servers, and they both report it independently, the standby is eligible to promotion again as soon as it’s caught-up with the primary again, and at this time it is assigned the SECONDARY state, and the replication will be switched back to synchronous.
Failure handling and network partition detection¶
If a node cannot communicate to the monitor, either because the monitor is down or because there is a problem with the network, it will simply remain in the same state until the monitor comes back.
If there is a network partition, it might be that the monitor and secondary can still communicate and the monitor decides to promote the secondary since the primary is no longer responsive. Meanwhile, the primary is still up-and-running on the other side of the network partition. If a primary cannot communicate to the monitor it starts checking whether the secondary is still connected. In PostgreSQL, the secondary connection automatically times out after 30 seconds. If last contact with the monitor and the last time a connection from the secondary was observed are both more than 30 seconds in the past, the primary concludes it is on the losing side of a network partition and shuts itself down. It may be that the secondary and the monitor were actually down and the primary was the only node that was alive, but we currently do not have a way to distinguish such a situation. As with consensus algorithms, availability can only be correctly preserved if at least 2 out of 3 nodes are up.
In asymmetric network partitions, the primary might still be able to talk to the secondary, while unable to talk to the monitor. During failover, the monitor therefore assigns the secondary the stop_replication state, which will cause it to disconnect from the primary. After that, the primary is expected to shut down after at least 30 and at most 60 seconds. To factor in worst-case scenarios, the monitor waits for 90 seconds before promoting the secondary to become the new primary.